Triple

T8515794
Position Surface form Disambiguated ID Type / Status
Subject Zack Snyder's Justice League E201567 entity
Predicate stars P1956 FINISHED
Object Gal Gadot E199710 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gal Gadot | Statement: [Zack Snyder's Justice League, stars, Gal Gadot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gal Gadot
Context triple: [Zack Snyder's Justice League, stars, Gal Gadot]
  • A. Gal Gadot chosen
    Gal Gadot is an Israeli actress and model best known internationally for portraying Wonder Woman in the DC Extended Universe films.
  • B. Ruby Rose
    Ruby Rose is an Australian model, DJ, and actress known for her androgynous style and roles in action films and television series such as "Orange Is the New Black."
  • C. Ana de Armas
    Ana de Armas is a Cuban-Spanish actress known for her breakout roles in films such as "Blade Runner 2049," "Knives Out," and "Blonde."
  • D. Margot Robbie
    Margot Robbie is an Australian actress and producer known for her versatile performances in films such as "The Wolf of Wall Street," "I, Tonya," and "Barbie."
  • E. Scarlett Johansson
    Scarlett Johansson is an American actress known for her versatile film roles, including major parts in the Marvel Cinematic Universe and acclaimed performances in both independent and blockbuster movies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ca8320e5748190ac2c585a0bba8193 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60f37b0819082ae14e539f57b56 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e5dbb3c81909157e6b04a4956af completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.